The paper deals with a flow shop scheduling problem, where energy costs are to be minimized with respect to time-varying electricity prices coming from the day-ahead market EPEX Spot Germany/Austria. To make efficient...
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The paper deals with a flow shop scheduling problem, where energy costs are to be minimized with respect to time-varying electricity prices coming from the day-ahead market EPEX Spot Germany/Austria. To make efficient use of the corresponding price volatility in the production planning phase, i.e., weeks prior to the start of production, price forecasts have to be incorporated into decision making. Since the suitability of mid-term electricity price forecasts for scheduling applications has not been clarified, we analyze forecasts from the literature for their usability by means of extensive scenarios as well as an appropriate evaluation scheme. Furthermore, solution methods are provided for the considered flow shop scheduling problem. We study a Fixand-Optimize and a priority rule-based sampling procedure in order to solve large-scale instances within a reasonable time. The performance analysis shows that Fix-and-Optimize achieves very good results in terms of solution quality. If production planners have to make quick decisions, the samplingprocedure provides excellent run times.
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